Today, minutiae-based and image-based are the two major approaches for the purpose of fingerprint authentication. Image based approach offers much higher computation efficiency with minimum pre-processing and proves also effective even when the image quality is too low to allow a reliable minutia extraction. However, this approach is vulnerable to shape distortions as well as variation in position, scale and orientation angle. In this paper, a novel method of image based fingerprint matching based on the features extracted from the integrated Wavelet and the Fourier-Mellin Transform (WFMT) framework is proposed to remedy these problems. Wavelet transform, with its energy compacted feature is used to preserve the local edges and reduce noise in the low frequency domain after image decomposition, and hence making the fingerprint images less sensitive to shape distortion. The Fourier-Mellin transform (FMT) served to produce a translation, rotation and scale invariant feature. Multiple WFMT features can be used to form a reference invariant feature through the linearity property of FMT and hence reduce the variability of the input fingerprint images. Based on this integrated framework, a fingerprint verification system is designed. The experiments show the verification accuracy is 5.66 and 1.01% of equal error rate is achieved when multiple WFMT features are used.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Vision and Pattern Recognition